NIH Record - National Institutes of Health

Knowledge Equals…?

NHGRI Alum Studies Reactions to Genomic Information

Dr. Saskia Sanderson
Dr. Saskia Sanderson

Photo:  Lisa Helfert

On the 15th anniversary of the founding of NHGRI’s Social and Behavioral Research Branch (and the 25th anniversary of the institute itself), one of SBRB’s first postdoctoral fellows—Dr. Saskia Sanderson, who arrived in 2007—returned to a kind of hero’s welcome recently when she explored the psychological impact of learning one’s personal genetic information during a talk in Lipsett Amphitheater.

It wasn’t like World Cup cheering in a soccer stadium, but it was a bit more boisterous than the usual welcome accorded speakers giving rounds. It was a homecoming after all, acknowledging the success of an alumnus—Sanderson has since gone on to research positions in Manhattan and, currently, in London.

A senior research associate at University College London, Sanderson discussed the utility of genome sequencing for physical and mental health—the balance of benefits versus risks that people compute internally when they stand to know more about their likelihood of disease than they would have had the human genome never been sequenced.

She described a patient, Paul, an otherwise healthy British double-bassist who smoked 20 cigarettes a day and suffered a heart attack at age 37. Would he have changed his behavior had he known his genetic risk of cardiovascular disease, Sanderson wondered?

Paul turned out to be Sanderson’s father, still alive, fortunately, and happy to be able to cavort with Sanderson’s young son.

With “tens of millions of people” expected to have their genomes sequenced in coming decades—there are already an estimated 25 million people worldwide participating in genome cohort studies—it is important to study the impact this new knowledge will have on individuals’ health and behavior, Sanderson believes.

She reviewed a number of studies undertaken in the past decade suggesting that when single genes are examined—such as GSTM1 as a marker for increased risk of lung and esophageal cancer—and a person’s risk is found to be relatively low, there is little impact on behavior.

“That’s a finding that has really permeated our field,” Sanderson said, “that testing doesn’t impact behavior.” It may, however, prompt initiation of medication and future screening.

Sanderson speaking at the podium.
“People have a hard time with risk. They want hard answers—yes or no. Communication is a big issue,” said Sanderson. “We have to work out how to talk to people about this. It’s an uncertain field.”

Photo:  Credit Lisa Helfert

After her NHGRI postdoc, Sanderson moved to Icahn School of Medicine at Mt. Sinai in New York City. She and her colleagues studied biobank enrollees’ attitudes toward taking part in genomic studies and eventually developed an online education tool to explain whole-genome sequencing to the public.

“We wanted to help people make decisions if they were invited to participate in genomic research.”

Another project called HealthSeq examined the utility of participating in genomic studies for people who were in good health. Thirty-five people had their genomes sequenced.

“At the end of the study, most people wanted a hard drive with their raw data, but no one knew what to do with it,” Sanderson reported.

Her studies have revealed some interesting dimensions of research participation:

  • Scientists want to include diverse populations for robust results, but people in Harlem, just north of Mt. Sinai, proved too under-insured to enroll; they could not afford the care they might need if something negative turned up.
  • Simple curiosity and concern about risk of disease motivate most people to participate in genetic studies.
  • As polygenic, rather than single-gene, risk scores become available, based on millions of common DNA variants, it will become even more important to evaluate the benefits vs. harms of such testing.

“We hope to be able to identify early those at risk of developing mental health problems,” Sanderson noted, “but the harm is the stigma involved…How do we maximize the benefits and minimize the harms?...We need to do this right, if we’re going to do it.”

During a brief Q&A session, Sanderson concluded, “None of this information is deterministic—it’s all about risk…People have a hard time with risk. They want hard answers, yes or no. Communication is a big issue. We have to work out how to talk to people about this. It’s an uncertain field.”

The talk was part of the NHGRI intramural program’s silver anniversary summer seminars, given by successful NHGRI trainees.

AI Applied in Clinical Settings

Dr. Dina Katabi talking at the podium.
Dr. Dina Katabi of MIT discusses AI innovations in clinical research and clinical care.

In addition to a disruptive keynote talk by tech thought leader Craig Mundie, the recent all-day artificial intelligence (AI) workshop heard a number of practical considerations and applications of machine learning in clinical settings that provided NIH with plenty of food for thought.

Dr. Dina Katabi of MIT’s Center for Wireless Networks and Mobile Computing introduced the “health-aware home,” her lab’s AI clinical application prototype.

Using the electromagnetic field surrounding everything, the group’s wi-fi-like technology can track and measure people’s breathing, sleep, heart rate, falls and gait speed—all without attaching sensors to the subject. The device transmits low-level wireless signals and uses AI to analyze the signals. It’s already been tested in assisted-living facilities with people who are elderly or who have sleep and breathing disorders, Parkinson’s disease or other chronic health problems.

“The future in health care is terrific,” Katabi said, “and computer science with additional technology, AI and machine learning will come together to provide much stronger types of data and also provide information for the health care system to improve the quality of care.

“Imagine what would happen if we had a device like this in the home of every chronic disease patient—how much more we would learn about diseases, how much more we would be able to intervene before exacerbation. I think we can do that if we start thinking together, bringing the computer scientists, people who work on AI, with people who are in the health care system—the doctors, the biologists, the bioengineers, the chemists—and creating that future.”

NIH’s own Dr. Ronald Summers of the Clinical Center offered proof that machine learning can significantly improve precision and accuracy in biomarker imaging diagnostics.

Dr. Judith Dexheimer of Cincinnati Children’s Hospital talked about her group’s research on making the wealth of data contained in electronic health records, or EHRs, more universally useful and accessible.

The event’s line-up also included intriguing talks by Eileen Koski of Microsoft, Dr. David Heckerman of Amazon and Dr. Anshul Kundaje of Stanford.

It’s clear that “we need to rather quickly escalate our involvement and our investment,” said NIH director Dr. Francis Collins, offering closing thoughts at day’s end.

Other action items he noted include the need to prioritize, harmonize and clean up data sets and better enforce provisions giving researchers access to such data; plan for quantum computing; and build a broader community for people in AI-related professions exploring health research applications.

Collins also said he intends to bulk up NIH’s brain trust, “deepening our own bench.” He’ll follow up the AI conference by convening a working group within his advisory committee to the director.

“We have a critical opportunity here now and we don’t want this moment to come up and go down without having some legs,” he concluded. “What exactly those legs should look like will have to involve some folks who can think big and give us big advice…

“We want our approach to AI to be more than just ‘A,’” Collins concluded. “The ‘artificial’ part comes really easily, but we need lots of ‘I,’ the intelligence part—and better yet, we need both of those together. And we’re only going to get there if you help us.”

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